Data Analyst Intern (Summer 2025)

As a Data Analyst Intern at Atlas Energy Solutions, your key responsibilities will include collecting and processing datasets from various sources, conducting analyses to identify trends and insights, and communicating your findings to departments like Accounting and Sales. You'll also track production work and build dashboards to monitor key metrics, which are critical in the oil and gas industry.

To qualify for the Data Analyst Intern position at Atlas Energy Solutions, candidates must be juniors or seniors currently pursuing a Bachelor's Degree. Strong proficiency in data analysis tools such as Excel, along with excellent analytical skills and attention to detail, are essential. Additionally, a willingness to learn and adapt to new technologies will greatly benefit your success in this role.

During your internship at Atlas Energy Solutions, you will primarily use Excel as your data analysis tool. However, you may also get the chance to work with other data visualization tools and software that will allow you to create insightful reports and dashboards, helping you develop a well-rounded skillset in data analysis.

The work environment for a Data Analyst Intern at Atlas Energy Solutions is dynamic and collaborative. Working onsite at our Austin headquarters, you'll be part of a supportive team that encourages learning and growth. You'll find that our culture emphasizes innovation, teamwork, and a commitment to excellence, providing a fantastic backdrop for your internship experience.

As a Data Analyst Intern at Atlas Energy Solutions, you'll be involved in projects that relate to production optimization and equipment maintenance within the oil and gas sector. Your analyses will support initiatives that improve efficiencies, manage logistics, and refine processes, offering you a captivating glimpse into the industry's operational aspects.

When approaching a data analysis project, I start by clearly defining the problem and the analysis objectives. I then gather and clean the data to ensure accuracy, followed by exploratory data analysis to identify trends. Once I have derived insights, I present my findings using visual dashboards, ensuring they are easy for stakeholders to understand and actionable.

I have extensive experience using Excel for data analysis, including creating complex formulas, pivot tables, and visualizations such as graphs and charts. I often utilize Excel's data tools for cleaning datasets and conducting analyses to derive meaningful insights effectively.

To ensure the accuracy of my data analyses, I follow a systematic approach that includes checking data integrity, validating results through cross-referencing with other datasets, and maintaining detailed documentation of my processes. By implementing best practices in data management, I can enhance the reliability of my findings.

In a previous project, I noticed a discrepancy in sales projections versus actual sales data. By analyzing the dataset and identifying patterns, I realized that seasonal trends were impacting our forecasts. I recommended adjustments based on my findings, which improved the accuracy of our projections significantly.

One challenge I faced was dealing with incomplete datasets. I tackled this by researching additional sources and leveraging techniques to fill in the gaps. I also improved communication with peers to understand data collection methods better, leading to more comprehensive and reliable analyses.

When facing tight deadlines, I prioritize tasks based on their impact and urgency. I break down the work into smaller, manageable steps, focusing on delivering quick wins while ensuring that my analyses maintain a high standard of quality. Communication with my team is key to managing expectations and ensuring that we stay aligned.

I have a preference for tools like Tableau and Power BI because they offer robust features for creating dynamic and interactive visualizations. These tools make it easy to present data insights in a clear and visually appealing manner, enhancing stakeholder engagement and facilitating data-driven decisions.

I work effectively in a team setting by maintaining open communication and being receptive to feedback. I actively participate in discussions and contribute ideas while also valuing my teammates' perspectives. I believe that collaboration leads to more innovative solutions and ensures that everyone feels involved and valued.

To explain complex data analysis to a non-technical audience, I focus on simplifying my terminology and using relatable examples. I would emphasize the key insights using visual aids like charts and graphs, highlighting the implications of the data analysis rather than getting bogged down in technical details.

I have experience presenting data findings to stakeholders through structured presentations that include visuals and clear narratives. I aim to engage my audience by telling a story with the data, using real-world implications of the findings to highlight their importance and encourage informed decision-making.